Hi Belle,
try this:
SAS:
proc mixed data=test noclprint noinfo covtest noitprint
method=reml;
class pair grade team school;
model score = trt pair grade school / solution ddfm=bw
notest;
random int / sub=team solution type=un r;
run;
R:
require(nlme)
unstruct <- gls(score~trt+pair+grade+school, test,
correlation=corSymm(form = ~ 1 |id),
weights=varIdent(form = ~ 1|team),
method="REML")
summary(unstruct)
--------------------------------------
Silvano Cesar da Costa
Departamento de EstatÃstica
Universidade Estadual de Londrina
Fone: 3371-4346
--------------------------------------
----- Original Message -----
From: "Belle" <ping...@gmail.com>
To: <r-help@r-project.org>
Sent: Thursday, January 27, 2011 5:43 PM
Subject: [R] HLM Model
Hi
I am trying to convert SAS codes to R, but some of the
result are quite
different from SAS.
When I ran proc mixed, I have an option ddfm=bw followed
by the model. How
can I show this method in R　(I am thinking that this maybe
the reason that I
can't get the similar results)
below is my SAS codes:
proc mixed data=test covtest empirical;
class pair grade team school;
model score = trt pair grade school/ solution covb ddfm=bw
;
random int / sub=team solution type=un;
run;
I have tried both lmer and hglm, but non of them works.
Could anyone tell me how can I covert this SAS codes to R?
Thanks
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and provide commented, minimal, self-contained, reproducible code.
